approved on marketing: a perspective from the …...increasing consumers’ hypermarket visit...

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Rev. Bras. Gest. Neg. São Paulo v.21 n.3 jul-set. 2019 p.435-463

REVISTA BRASILEIRA DE GESTÃO DE NEGÓCIOS ISSN 1806-4892REVIEw Of BuSINESS MANAGEMENT e-ISSN 1983-0807RBGN

Review of Business Management

DOI: 10.7819/rbgn.v21i3.4008

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Received on07/06/2017Approved on12/27/2018

Responsible editor: Prof. Dr. Guilherme de Farias Shiraishi

Evaluation process: Double Blind Review

Increasing Consumers’ Hypermarket Visit Intention through Cause-Related

Marketing: A Perspective from the Theory of Planned Behaviour

Kay Tze Hong1

Siew Imm Ng1

Raja Nerina Raja Yusof1

1University Putra Malaysia, Department of Marketing and Management, Serdang and Malaysia

Shivee Ranjanee Kaliappan2

2University Putra Malaysia, Department of Economics, Serdang and Malaysia

Abstract

Purpose – This study intends to discover factors affecting consumers’ intention to participate in cause-related marketing (CRM) and how CRM influences their intention to visit hypermarkets in Malaysia.

Design/methodology/approach – Through a self-administered questionnaire and using a mall-intercept technique, a total of 460 samples were collected from consumers in Malaysia. Structural equation modelling was then used to analyse the data.

Findings –The results show that three variables (perceived CSR image, consumer–company identification and perceived company–cause fit) out of four significantly predicted consumers’ attitude towards CRM. Also, two components (attitude and perceived behavioural control) out of three in the theory of planned behaviour were found to be significantly related to CRM participation intention. Lastly, CRM participation intention was found to influence hypermarket visit intention.

Originality/value – The proposed theory of planned behaviour (TPB) was found to be applicable in predicting CRM participation intention and hypermarket visit intention. The findings showed that consumers are more likely to increase their intention to visit a hypermarket that adopts a CRM campaign, which led us to highlight the main implications for hypermarket management and new study areas in this field.

Keywords – corporate social responsibility; cause-related marketing; hypermarket; visit intention; theory of planned behaviour

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Kay Tze Hong / Siew Imm Ng / Raja Nerina Raja Yusof / Shivee Ranjanee Kaliappan

1 Introduction

The Malaysian retail sector is recognised as being the main contributor to the nation’s gross national income (GNI) and has transformed throughout the years from small traditional retail shops to large modern retail format stores, such as hypermarkets, supermarkets and department stores (PEMANDU, 2013). Although Malaysia has faced weak economic conditions, grocery retailing has remained strong in its value growth (Euromonitor International, 2014). The resilience of the retail sector under such economic conditions attracts many players and creates intense competition. Therefore, retailers, including hypermarkets, need to manage consumers’ expectations more effectively to remain relevant.

Given the increased awareness of corporate social responsibility (CSR) in general, consumers have expected hypermarkets to start showing initiatives in CSR-related activities (Saeidi et al., 2015). CSR has innovatively emerged as part of a firm’s marketing strategy by linking CSR activities to sales objectives; this is called cause-related marketing (CRM). CRM has been welcomed by companies because it has fulfilled consumers’ expectations and improved company performance and reputation while helping a social cause (Sen & Bhattacharya, 2001). The applicability of CRM in the hypermarket context is under-reported. So far, CRM research has largely focused on specific retailers (Liu & Ko, 2011), such as chocolate manufacturers (Moosmayer & Fuljahn, 2010), fast-moving consumers goods (Patel et al., 2017), hotels (Boenigk & Schuchardt, 2015) and restaurants (Hanks et al., 2016).

This study on CRM differs from others in two ways. First, others have focused on social cause or product factors, such as the influence of the social cause category on consumer perceptions (Lafferty & Edmondson, 2014) and products of CRM with negative externalities possibly leading to unexpected effects (Grolleau et al., 2016). The literature that has looked at consumer and firm

factors such as consumers’ CRM attitude and the firm’s CSR image is limited. Second, the research framework of CRM has so far focused on loose antecedents that directly affect CRM intention. In fact, many of these antecedents were factors that formed attitude towards CRM and attitude was reported to be the main driver of intention (Pookulangara et al., 2011), which is consistent with the proposal of the theory of planned behaviour (TPB). TPB may serve as a theoretical basis to understand CRM antecedents more meaningfully, but its use in the CRM context is scarce. Therefore, this study closes the gap in the literature by testing the applicability of TPB in explaining consumers’ CRM participation intention and hypermarket visit intention.

This study investigates the effectiveness of CRM in consumers’ hypermarket visit intention using the TPB model. Its components, namely attitude, subjective norm (SN) and perceived behavioural control (PBC), are used to evaluate consumers’ response to CRM and hypermarket visit intention. This study contributes to the literature in three ways. First, it uses a novel social cause called “supporting underprivileged individuals”, which has the ultimate aim of developing financially independent entrepreneurs. This social cause was created by this study based on suggestions from a focus group interview (forthcoming paper). The CRM literature has commonly focused on causes including diseases such as cancer (Robinson et al., 2012), wildlife and environmental causes such as the World Wildlife Fund and rainforest protection (Chéron et al., 2012), and the homeless (Chang, 2011).

The cause of supporting underprivileged individuals is relevant to a developing country like Malaysia as income distribution inequality is still high (The Star Online, 2013) and lower income groups need additional attention (The Star Online, 2016). Underprivileged individuals include single mothers, unskilled individuals and individuals that lack access to proper resources and food (Borneo Post Online, 2013; Malay Mail Online, 2016). By helping the underprivileged to

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Increasing Consumers’ Hypermarket Visit Intention through Cause-Related Marketing: A Perspective from the Theory of Planned Behaviour

support themselves, the country is also able to rise above the poverty line as a whole.

Second, the study contributes to the CRM literature by introducing a framework with a stronger theoretical background, that is, TPB. So far, CRM frameworks have not been rooted in a solid theoretical base. For example, most CRM studies have used multiple supporting theories, such as social identity theory (Vanhamme et al., 2012), attribution theory (Cui et al., 2003) and information integration theory (Samu & Wymer, 2009), to explain individual construct relationships with consumers’ response to CRM. Third, the study extends the use of CRM to the hypermarket context. The applicability of CRM in the hypermarket context can provide valuable insights for hypermarket managers. The antecedents, namely altruistic firm motives (AFM), consumer–company identification (CCI), perceived CSR image (CSRI) and perceived company–cause fit (CCF), are hypothesised to influence attitudes towards CRM, which can help managers make informed decisions on CRM implementation.

2 Literature review

2.1CSR and CRM

CSR is a tactic not only for fulfilling a company’s moral obligation to the community, but also a way for the firm to align its interests with its stakeholders’ to decrease risks and safeguard the continuity of the company’s business (de Freitas Brandão et al., 2017). Patrus et al. (2013) asserted that a socially responsible company creates organizational values and seeks to improve the social conditions of people affected by its actions. Likewise, retailers that participate in CSR activities can positively enhance the relationship between retailer and customer (Potdar, Guthrie & Gnoth, 2018). CSR has been studied from many different perspectives and in contexts such as the relationship between CSR and employees’ perceptions (e.g. Azim, 2016; de Freitas Brandão et al., 2017), the positive influence of ownership concentration on CSR

(Crisóstomo & Freire, 2015) and the relationship between consumers’ CSR perception and social boycott (Cruz, 2017). This study focuses on the dimension of consumers’ perceptions regarding the hypermarket’s CSR initiatives (i.e. CRM) and its positive impact on consumers’ hypermarket visit intention, because CRM is currently under-researched.

CRM is one of the CSR activities carried out by companies (Anuar & Mohamad, 2012). CRM is the focus of this study because it is recognised as the most creative, cost-effective and popular marketing strategy (Galan Ladero et al., 2015). Varadarajan and Menon (1988) defined CRM as an action that creates and employs marketing activities through the proposal that a firm donates a designated sum of funds to a chosen social cause in exchange for revenue-providing activities through purchase of the company’s products or services. The increased adoption of CRM by many organizations has mainly been due to the various benefits that companies could gain, such as improved sales and profits as well as enhanced corporate and brand image (Anuar & Mohamad, 2011). CRM can help companies draw more consumers, escalate sales and enhance their favourable image with the public (Anghel et al., 2011).

CRM manages to bring a company and its consumers closer through their shared moral values and societal integrity (Soni & Soni, 2013). For example, Langen et al.’s (2013) study reported that 93% of consumers purchased a CRM product because they felt that doing something good was important. Therefore, CRM can be a source of competitive advantage for companies that intend to differentiate themselves from others and attract more consumers. The present study evaluates whether CRM could be used by hypermarkets to improve their performance in terms of increased consumer visits.

2.2 Theory of Planned Behaviour

One of the models that is widely used to predict the intention and behaviour of consumers

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is TPB (Ajzen, 1991). TPB indicates that attitude, subjective norm and perceived behavioural control influence intention and, in turn, behaviour (Ajzen, 1985). Attitude towards a behaviour is defined as the extent to which an individual has a positive or negative perception of the behaviour. Subjective norm is defined as the perception of social pressure to perform or not perform the behaviour (Verbeke & Vackier, 2005). Perceived behavioural control is defined as the perception of how well an individual can control the factors that support or hinder the actions required to handle a particular situation (Han et al., 2010). Intention is defined as the likelihood of a person to behave in a particular way (Fishbein & Ajzen, 1975). Most empirical applications of TPB have explained and predicted human behaviour in various areas to understand the relationships among attitude, SN, PBC and behavioural intention, such as studies related to food choice (e.g. Lorenz et al., 2015), tourism decisions (e.g. Hsu & Huang, 2012), online buying (e.g. Yusta et al., 2011) social entrepreneurial intention (e.g. Cavazos-Arroyo et al., 2017) and consumers’ shoplifting prevention behaviour (e.g. Potdar et al., 2018). However, TPB has not been used in the context of consumers’ participation intention regarding CRM.

TPB may enhance the prediction of consumers’ participation intention regarding CRM and hypermarket visit intention. Ajzen (1991) stated that a person’s attitude is established by behavioural beliefs, which suggests that some cognitive motivation or factors could affect attitude. In addition, research points to the fact that attitude gives the highest explained variance of intention (e.g. Lam & Hsu, 2006; Pookulangara et al., 2011). Therefore, in this study, aside from applying the proposed determinants of TPB (i.e. attitude, SN and PBC), the antecedents of attitude towards the CRM campaign, such as AFM, CSRI, CCI and CCF, are also explored. These four variables were chosen for this study based on a brief pilot study with 10 faculty members, asking them about their motivation to participate in CRM, from which these four variables emerged

as main themes. Also, the same four factors have been consistently supported in the literature for explaining CRM intention (e.g. Moosmayer & Fuljahn, 2013; Lii & Lee, 2012; Deng & Xu, 2017; Samu and Wymer, 2009). Thus, this gives a richer understanding of the factors influencing consumers’ CRM participation and hypermarket visit intention. This study is similar to that of Cavazos-Arroyo et al. (2017), which extended the traditional TPB model by including the antecedents (e.g. social vision, sustainable values, financial return interests) of social entrepreneurial attitudes.

In short, despite the vast amount of empirical work on CRM, an understanding of the effects of the TPB factors on CRM participation intention and consumers’ hypermarket visit intention is lacking. The present study extends TPB by taking into account the antecedents to attitude aside from the three TPB factors (attitude, SN and PBC).

3 Theoretical framework

3.1Altruistic Firm Motives (AFM)

Moosmayer and Fuljahn (2013) reported that the perceived firm motive influences consumers’ assessment and attitude towards CRM and further affects consumers’ decision to participate in a CRM campaign. Specifically, a profit-oriented motive is usually evaluated as unfavourable by consumers, whereas an altruistic motive is evaluated positively. Similarly, a retailers’ altruistic social image may enhance the retailer-customer relationship (Potdar et al., 2018). Ellen et al. (2000) found that consumers show a more positive response to a CRM campaign when they believe that the firm’s motives are intrinsically (genuine help) rather than extrinsically (profit-related) motivated. The hypermarket’s CRM campaign communication in this study is designed in such a way that “other–serving” aspects are prominent. For example, taglines such as “promote sustainable economics and empower individuals” (see Appendix I) are used on the boards. In short, when a hypermarket’s motive

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is deemed to be altruistic (other-serving) by consumers, they exhibit a more positive attitude towards the CRM campaign, which leads to the development of the following hypothesis:

H1: A positive relationship exists between an altruistic firm motive and consumers’ attitude towards a CRM campaign.

3.2Consumer-Company Identification (CCI)

An important source of social identity is membership of diverse social groups and relationships with various organizations (Kang et al., 2015). For instance, organizational identification happens when employees’ beliefs about their organization become incorporated into their self-concept, and the employees see themselves as exemplifying the organization (Azim, 2016; Cavazotte et al., 2017). This relationship can also be applied in the consumers’ setting, where consumers’ desire for a sense of belonging can build a socially identifying relationship with a company (Brewer, 1991). Consumers psychologically define themselves as part of the company by internalising the company’s conventional norms as personal norms, leading to a favourable attitude towards that company (Curra´s-Pe´rez et al., 2009). Similarly, when consumers have a high CCI with a hypermarket, they have a higher tendency to help in the hypermarket’s success, and thus tend to have a positive attitude regarding the activities organized by the hypermarket, including the CRM campaign (Lii & Lee, 2012). Therefore, the following hypothesis is presented:

H2: A positive relationship exists between consumer-company identification and consumers’ attitude towards a CRM campaign.

3.3Perceived CSR image (CSRI)

Lacey et al. (2015) defined perceived CSR as consumers’ assessment of a company’s achievements in meeting its stakeholder

expectations and its societal obligations by being involved in various charitable activities. An unfavourable CSR image perceived by consumers may lead to negative outcomes for the company such as boycotting (Becker-Olsen et al., 2006), while a favourable CSR image perceived by consumers leads to a positive effect on purchase intention, recommend intention and loyalty (Deng & Xu, 2017). According to Park et al. (2017), when consumers perceive that a company has high ethical standards, they believe that the firm is committed to its CSR initiatives. Therefore, when consumers perceive that the previous CSR activities implemented by a hypermarket reveal a favourable CSR image, they are more inclined to have a positive attitude towards the current CRM campaign. Thus, the following hypothesis is presented:

H3: A positive relationship exists between the perceived CSR image of the hypermarket and consumers’ attitude towards the CRM campaign.

3.4Perceived Company–Cause Fit (CCF)

A high CCF reflects an apparent relationship between a company’s core business and its designated social cause. Accordingly, Van den Brink et al. (2006) asserted that a CRM campaign with a high CCF has a 5–10 times greater effect than one with a low CCF. When the company and cause seem complementary as the latter fits the company’s identity, consumers perceive the company’s CSR activities to be genuine (Alhouti et al., 2016). Samu and Wymer (2009) found that a higher fit led to a more favourable attitude and behavioural intention. When a CRM campaign shows a high CCF, consumers perceive that the campaign message may enhance the sustainability of the company and find helping to be reasonable. In the case of the cause used by this study, the underprivileged individuals are trained to be entrepreneurs who supply products to the hypermarkets, and increase local content variety. Therefore, consumers may

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form a favourable attitude towards the CRM campaign. The following hypothesis is derived:

H4: A positive relationship exists between company–cause fit and consumers’ attitude towards a CRM campaign.

3.5CRM Participation Intention and Hypermarket Visit Intention

TPB implies that intention is the most important predictor of behaviour (Arvola et al., 2008), and behavioural intention is known to be a function of attitude, SN and PBC (Ajzen, 1991). Therefore, the greater the attitude, SN and PBC, the stronger a person’s intention to perform that particular behaviour is (Bamberg et al., 2003). Firstly, when an individual has a favourable attitude towards a specific behaviour, the individual’s intention to engage in the behaviour is enhanced (Ajzen, 1991). For example, a significant relationship was found between the attitude of young adults towards advertising and their intention regarding advertising (Ting et al., 2015). Therefore, this study predicts that consumers with a positive attitude towards a CRM campaign are more likely to have a stronger intention to participate in it.

Secondly, Han et al. (2010) defined subjective norm as the probability of whether important referents agree or disagree with the behaviour. It was found that SN influenced intention to purchase through the internet (Yusta et al., 2011). In this study, when people around the individual think that a CRM campaign is a good way to help a worthy cause, then the individual’s perceived social pressure to participate in the CRM campaign intensifies. Thirdly, perceived behavioural control is low when an individual has little control over executing a specific behaviour because of the lack of access to essential resources. Wu et al. (2016) found

that PBC plays the most significant role in explaining senior citizens’ intention in relation to physical activities in Taiwan. In this study, when consumers feel that they have full control over the decision to participate in a CRM campaign because of sufficient resources such as time and money, they are more likely to participate in the CRM campaign.

The literature implies that intention is significantly correlated with behaviour. Graham-Rowe et al. (2015) pointed out that the greater a person’s intention to execute a behaviour, the greater the likelihood that the behaviour would be performed. Therefore, in this study, CRM participation intention is viewed as a motivation factor in the decision to visit a hypermarket that implements CRM. Evidence shows that consumers tend to buy from a company with CRM (Langen et al., 2013). Therefore, consumers’ hypermarket visit intention increases because they want to support a CRM campaign. The following hypotheses are derived:

H5: A positive relationship exists between attitude towards CRM and consumers’ participation intention regarding the CRM campaign.

H6: A positive relationship exists between subjective norm and consumers’ participation intention regarding the CRM campaign.

H7: A positive relationship exists between perceived behavioural control and consumers’ participation intention regarding the CRM campaign.

H8: A positive relationship exists between consumers’ participation intention regarding the CRM campaign and consumers’ hypermarket visit intention.

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Figure 1 - Conceptual Framework

4Research methodology

4.1Data Collection and Sampling

Data were gathered from consumers in Malaysia during the month of February in 2017 using a self-administered questionnaire method. The questionnaire was adapted from established past literature and was back-translated to Malay and Mandarin by the first author of the paper. Then, the questionnaire was back-translated into English by two other authors to create translation validity following the approach suggested by Brislin (1970). After that, the questionnaires were distributed to consumers in malls in three states of Malaysia (Selangor, Federal Territory of Kuala Lumpur & Putrajaya, and Johor) using the mall-intercept approach. Respondents were intercepted in the malls by asking whether they would be willing to participate in a research survey and the respondents who agreed to participate were given the questionnaire to be completed on the spot. Upon completion, the respondent was given a RM20 (about USD5) cash voucher as a token of appreciation. A total of six malls were approached, three located in urban areas and three in sub-urban areas. Two malls (one urban and one sub-urban) were selected from each state. The three states (Selangor, Federal Territory of Kuala Lumpur & Putrajaya, and Johor) were chosen for data collection because they have the highest numbers of hypermarket outlets (top three highest) (Department of Statistics Malaysia, 2011).

The respondents were asked to rank their most preferred hypermarket (most frequently visited) ranging from 1 to 5 (e.g. Giant, Tesco, AeonBig, Mydin and NSK) and were required to read a hypothetical CRM campaign based on their most preferred hypermarket (Appendix 1) before filling in the questionnaire. In other words, the respondent’s most preferred hypermarket would be the hypermarket that they may identify with, as it is their most frequently visited hypermarket. Also, the social cause (supporting underprivileged individuals) in Appendix 1 was selected because the NGO’s (CASE) aim was to develop or train these underprivileged individuals in entrepreneurship skills so that they could survive on their own by starting small businesses in their community. This cause is associated with the hypermarkets, where products produced by these underprivileged individuals may be future supplies of the hypermarkets.

4.2Respondents

The final sample consisted of 460 consumers, 58.4% of whom were females. Most of the respondents were Malays (47%), followed by Chinese (33%) and Indians (18.5%). The majority of the respondents were aged 31–40 years old (32.4%). Almost half had obtained a bachelor’s degree (47.8%). This is consistent with Malaysia’s Ministry of Education Graduate Tracer Study 2015, where 45% of Malaysian graduates hold a Bachelor’s Degree and Diploma (The Ministry of Higher Education and Bank

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Negara Malaysia, 2017). Moreover, the results in Appendix 2 indicated no significant differences in hypermarket visit intention and CRM participation intention across the various educational groups. In addition, most of them had a monthly income of RM2000–RM4000 (USD483.27 – USD966.54) (32.4%). This is in line with the findings of the Department of Statistics of Malaysia, which stated that the average monthly wage of Malaysians in 2017 was about RM2,880 (USD696.83) (The Star Online, 2018).

An additional analysis was performed to uncover differences in hypermarket visit intention and CRM participation intention across the various respondent profiles, such as gender, education level and monthly income. An independent sample T-test and one-way ANOVA

were employed for this purpose and the results are shown in the tables of Appendix 2. There were no significant differences in hypermarket visit intention between genders, educational levels and income levels. As for CRM participation intention, no differences between genders and educational levels were found, but there was a difference between income groups. Apparently, those with a higher income (RM12000 – 16000) (USD2904 – 3871) were significantly more likely to participate in CRM than other income groups.

4.3 Measures

This study used a seven-point Likert scale (from strongly disagree to strongly agree) to measure the constructs. Table 1 provides the list of sample items and their references, where the items were adapted from.

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Table 1 Sample items of measurement instrument

Construct Sample Items Authors

Altruistic Firm Motives

AFM1 Pure (Sincere) Six items from Folse, Niedrich and Grau (2010)AFM2 Unselfish

Consumer–Company Identification

CCI1 This hypermarket’s principle is similar to my values. Six items from Mael and Ashforth (1992)and Wu and Tsai (2008)

CCI2 When someone praises this hypermarket, it feels like a personal compliment.

Perceived CSR Image

CSRI1 I think this hypermarket has a legitimate (genuine/sincere) interest in this cause.

Five items from Folse et al. (2010)

CSRI2 This hypermarket is socially responsible.

Perceived Company–Cause Fit

CCF1 The “supporting underprivileged individuals” cause implemented by this hypermarket fits with the nature of its business.

Three items from Ellen, Webb and Mohr (2006)

CCF2 The “supporting underprivileged individuals” cause implemented by this hypermarket is relevant to its business.

Attitude ATT1 I like the idea of buying products from a hypermarket which donates part of its profits to a social cause or NGO.

Four items from Kropp, Holden and Lavack (1999)

ATT2 I am willing to pay more for a product from a hypermarket if the hypermarket is donating part of the profits to a social cause.

Subjective Norm SN1 The trend of purchasing products from a hypermarket that supports a social cause among people around me is increasing.

Four items from Al-Swidi, Mohammed Rafiul Huque, Haroon Hafeez and Noor Mohd Shariff (2014)

SN2 People around me generally believe that it is a good idea to purchase products from a hypermarket that supports a social cause.

Perceived Behavioural Control

PBC1 I can make the decision independently to purchase products from a hypermarket that supports a social cause.

Five items from Al-Swidi et al. (2014)

PBC2 I have the financial capability to purchase products from a hypermarket that supports a social cause.

CRM Participation Intention

CRMPI1 I think this hypermarket’s campaign for “supporting underprivileged individuals’ is a good idea.

Four items from Folse et al. (2010)

CRMPI2 I would be willing to participate in this hypermarket’s campaign for “supporting underprivileged individuals” by buying most of my groceries from this hypermarket.

Hypermarket Visit Intention

HVI1 I would recommend this hypermarket that “supports underprivileged individuals” to someone who seeks my advice.

Four items from Grewal, Baker and Voss (2003), Olorunniwo, Hsu and Udo (2006)

HVI2 I would say positive things about this hypermarket that “supports underprivileged individuals” to other people.

4.4 Data Analysis

To analyse the research model, this study employed the partial least squares (PLS) - structural equation modelling (SEM) analysis technique using SMARTPLS 3.2.3 (Ringle et al., 2015). As recommended by Anderson and Gerbing (1988), this study applied the two-stage analytical procedure: measurement model (validity and reliability of the measures) and structural model (hypothesised relationship

testing) (Hair et al., 2014). In the PLS-SEM, the model evaluations used the R-squared values for evaluating endogenous variables and effect size, while significance levels and t-values were used to evaluate the structural path coefficients (Fornell & Cha, 1994). Moreover, the estimations of standard errors and t-values were derived by performing a bootstrapping resampling technique with 1,000 resamples (Chin, 1998).

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5Results and analysis

5.1Measurement Model Validation

This study assessed the measurement model by examining two types of validity, namely convergent validity and discriminant validity. Convergent validity of the measurement model is generally verified by determining the loading, Cronbach’s alpha, composite reliability and average variance extracted (AVE) (Gholami et al., 2013). As shown in Table 2, the indicators’ outer loadings for all items exceeded the recommended value of 0.5 (Hair et al., 2010). The Cronbach’s alpha values of all constructs were above 0.7, which indicates internal consistency (Nunnally & Bernstein, 1994). The composite reliability values had a range of 0.887–0.952, which was greater than the threshold level of 0.7 (Hair et

al., 2010). The AVE had a range of 0.628–0.831, which was greater than the cut-off value of 0.5 (Hair et al., 2010).

After that, discriminant validity was then examined by following the Fornell and Larcker (1981) criterion. As shown in Table 3, the square root of the AVE was denoted by the bold values on the diagonal. These values exceeded the off-diagonal values of the corresponding row and column, thus demonstrating that the measures were discriminant. In conclusion, both convergent and discriminant validity were established. Additionally, the standardised root mean square residual (SRMR) was tested to examine the model fit. The threshold value of below 0.08 is considered a good fit (Hu & Bentler, 1999). The model in the current study obtained an SRMR value of 0.058, which indicated a good fit.

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Table 2 Measurement model: loadings, construct reliability and convergent validity

Construct/Indicator Loading Composite reliability (CR) Cronbach’s alpha Average variance

extracted (AVE)Altruistic Firm Motives 0.914 0.888 0.640AFM1 0.793AFM2 0.814AFM3 0.851AFM4 0.787AFM5 0.773AFM6 0.777Consumer–Company Identification 0.910 0.884 0.628CCI1 0.728CCI2 0.829CCI3 0.792CCI4 0.817CCI5 0.825CCI6 0.760Perceived CSR Image 0.925 0.898 0.712CSRI1 0.834CSRI2 0.868CSRI3 0.875CSRI4 0.866CSRI5 0.770Perceived Company–Cause Fit 0.921 0.871 0.795CCF1 0.890CCF2 0.905CCF3 0.880Attitude 0.887 0.829 0.665ATT1 0.801ATT2 0.702ATT3 0.897ATT4 0.850Subjective Norm 0.926 0.893 0.757SN1 0.843SN2 0.872SN3 0.893SN4 0.870Perceived Behavioural Control 0.900 0.862 0.644PBC1 0.834PBC2 0.849PBC3 0.845PBC4 0.771PBC5 0.704CRM Participation Intention 0.924 0.889 0.753CRMPI1 0.792CRMPI2 0.877CRMPI3 0.911CRMPI4 0.885Hypermarket Visit Intention 0.952 0.932 0.831HVI1 0.906HVI2 0.908HVI3 0.925HVI4 0.907

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Table 3 Discriminant validity of the measurement model: Fornell and Larcker (1981)

ATT CRMPI CSRI CCF CCI AFM PBC SN HVIATT 0,816

CRMPI 0,696 0,868

CSRI 0,559 0,549 0,844

CCF 0,522 0,531 0,632 0,892

CCI 0,457 0,488 0,591 0,607 0,793

AFM 0,493 0,498 0,777 0,573 0,529 0,800

PBC 0,672 0,588 0,517 0,493 0,488 0,448 0,802

SN 0,632 0,521 0,516 0,553 0,582 0,456 0,611 0,870

HVI 0,682 0,641 0,469 0,441 0,376 0,422 0,586 0,484 0,912

Note: Diagonals represent the square root of the AVE, and the off-diagonals represent the correlations.

5.2 Descriptive Statistics (Mean, Standard Deviation, Skewness and Kurtosis)

Table 4 shows the descriptive statistics and normality test of the constructs. Based on the result, the CRM factors (Altruistic Firm Motives, Consumer-Company Identification, Perceived Corporate Social Responsibility Image, and Perceived Company-Cause Fit) that would motivate consumers to participate in a CRM campaign recorded mean scores above 4 on a 7-point Likert scale (where 1 = Strongly Disagree and 7 = Strongly Agree). In other words, the respondents agreed that their preferred hypermarket exhibited altruistic firm motives, consumer-company identification, a perceived corporate social responsibility image, and a perceived company-cause fit.

Similarly to the theory of planned behaviour elements (attitude, subjective norms and perceived behavioural control), the respondents generally showed that attitude towards CRM (M=5.302), subjective norms (M=5.019), and perceived behavioural control (M=5.175) were

high in the context of the hypermarket CRM on a 7-point Likert scale (where 1 = Strongly Disagree and 7 = Strongly Agree). The respondents also showed that they have strong intentions to participate in a CRM campaign (M = 5.347). Table 4 also shows that the respondents have strong intentions to visit a hypermarket that implements a CRM campaign (M = 5.390).

Hair et al. (2014) asserted that absolute skewness and/or kurtosis values of within +/- 1 are indicative of highly normal data. As presented in Table 4, all the constructs were within the acceptable skewness range except two constructs (perceived behavioural control and hypermarket visit intention) which did not meet the acceptable kurtosis range. However, the non-normal distribution problem is not an issue with PLS-SEM as it statistically provides a very resilient model of estimations with normal and extremely non-normal data (i.e., skewness and/or kurtosis) distributional properties (Reinartz, Haenlein & Henseler, 2009) by employing the bootstrapping technique.

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Table 4 Descriptive Statistics (Mean, Standard Deviation, Skewness and Kurtosis)

Skewness Kurtosis

No. Constructs Mean Standard Deviation

Statistic Std. Error Statistic Std. Error

1 Altruistic Firm Motives 5.186 0.863 -0.136 0.114 -0.371 0.2272 Consumer–Company Identification 4.698 0.991 -0.563 0.114 0.504 0.2273 Perceived CSR Image 5.110 0.945 -0.439 0.114 0.352 0.2274 Perceived Company–Cause Fit 5.011 0.922 -0.078 0.114 0.042 0.2275 Attitude 5.302 0.932 -0.442 0.114 0.612 0.2276 Subjective Norm 5.019 0.983 -0.415 0.114 0.253 0.2277 Perceived Behavioural Control 5.175 0.919 -0.624 0.114 1.105 0.2278 CRM Participation Intention 5.347 0.960 -0.622 0.114 0.703 0.2279 Hypermarket Visit Intention 5.390 0.952 -0.632 0.114 1.308 0.227

5.3 Structural Model Assessment

Hypothesis testing in this study was performed by evaluating the structural model. The coefficient of determination (R2), the beta and the corresponding t-values were assessed by running a bootstrapping procedure with 1,000 resamples (Hair et al., 2014). Aside from these basic measures, predictive relevance (Q2) and effect sizes (f2) were also reported (Hair et al., 2014). As shown in Table 5, six out of the eight hypotheses were supported. Firstly, CCI (β = 0.103, t-value > 1.645), CSRI (β = 0.288, t-value > 1.645) and CCF (β = 0.229, t-value > 1.645) were all positively related to attitude towards CRM. Thus, H2, H3 and H4 were supported but not H1 (AFM; β = 0.083, t-value < 1.645). In total, CCI, CSRI and CCF explained 36.9% of the variance in attitude. Secondly, attitude (β = 0.519, t-value > 1.645) and PBC (β = 0.194, t-value > 1.645) were positively related to CRM participation intention. Therefore, H5 and H7 were supported but not H6 (SN; β = 0.075, t-value < 1.645). Overall, attitude and PBC explained 51.4% of the

variance in CRM participation intention. Lastly, CRM participation intention (β = 0.641, t-value > 1.645) was positively related to hypermarket visit intention, explaining 41% of the variance in hypermarket visit intention. Thus, H8 was supported. The R2 values all exceeded the 0.35 value, which implies a substantial model, as suggested by Cohen (1988).

The effect sizes (f2) were also assessed. Cohen’s (1988) guideline was used to measure the degree of effect sizes, which are trivial (< 0.02), small (0.02), medium (0.15) and large (0.35). As shown in Table 5, six relationships showed substantive effects (i.e. one trivial effect size, three small effect sizes, one medium effect size and one large effect size). Using a blindfolding procedure, this study examined the predictive relevance of the model. Table 5 shows the three Q2 values for attitude (Q2 = 0.241), CRM participation intention (Q2 = 0.382) and hypermarket visit intention (Q2 = 0.339). All values were above 0, which implies that the model has sufficient predictive relevance (Hair et al., 2014; Fornell & Cha, 1994).

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Table 5 Results of the structural model analysis (hypotheses testing)

Hypothesis Relationships Standard Beta

Standard Deviation t-value Decision R2 f2 Q2

H1 AFM ATT 0,083 0,072 1,156 Not Supported 0,369 0,004 0,241

H2 CCI ATT 0,103 0,058 1,773* Supported 0,009

H3 CSRI ATT 0,288 0,075 3,868** Supported 0,043

H4 CCF ATT 0,229 0,063 3,661** Supported 0,042

H5 ATT CRMPI 0,519 0,053 9,827** Supported 0,514 0,261 0,382

H6 SN CRMPI 0,075 0,059 1,269 Not Supported 0,006

H7 PBC CRMPI 0,194 0,059 3,281** Supported 0,038

H8 CRMPI HVI 0,641 0,043 14,847** Supported 0,410 0,696 0,339

Note: * p < 0.05; ** p < 0.01

AFM Altruistic Firm Motives, CCI Consumer–Company Identification, CSRI Perceived CSR Image, CCF Perceived Company–Cause Fit, ATT Attitude towards CRM, SN Subjective Norm, PBC Perceived Behavioural Control, CRMPI Cause-Related Marketing Participation Intention, HVI Hypermarket Visit Intention

6Discussion

Grounded in the theory of planned behaviour, this study determined the factors affecting CRM participation and hypermarket visit intention of consumers in Malaysia. As attitude plays the most significant role in explaining intention (e.g. Luna et al., 2017; Ting et al., 2015), this study identified the antecedents to attitude. The result shows that CCI, CSRI and CCF significantly affect attitude towards CRM participation intention. This finding is in accordance with those of Lii and Lee (2012), Deng and Xu (2017) and Van den Brink et al. (2006). However, this study did not find support for the effect of AFM on CRM participation intention. This outcome could be due to the fact that Malaysian consumers find it difficult to evaluate the motives of firms. Consumers are confused about the motives of hypermarkets in Malaysia as Malaysian government agencies (e.g. Ministry of Domestic Trade and Consumer Affairs) have been actively driving campaigns where hypermarkets are expected to co-organize. Some of these projects, which help SMEs’ products get placed in hypermarkets. Consumers may think that hypermarkets participate in these government-driven campaigns due to compliance obligations.

Thus, hypermarket motives may be masked by compliance issues, which make it difficult for consumers to assess the altruistic levels of hypermarkets when organizing CRM campaigns. Furthermore, the insignificant effect of altruistic firm motives on attitude could be due to the fact that the impact of altruistic firm motives on attitude is overlapping with perceived corporate social responsibility. Altruistic firm motives and perceived corporate social responsibility has a correlation coefficient of 0.777 (Table 3), which indicates that these two dimensions are very similar in the eyes of respondents.

Various fields of research have used TPB to predict behavioural intention. Most of them have found attitude to have the strongest effect (e.g. Hsu et al., 2017; Luna et al., 2017). The same result is found in this study, in which attitude has the strongest effect on intention relative to SN and PBC. The power of attitude is prominent and most likely due to the relatively new introduction of CRM in hypermarkets, which usually arouse consumers’ curiosity and are prone to acceptance. It is also probably because of the good cause that the hypermarket is involved in, which gives a sense of social responsibility fulfilment to consumers and an impression that the hypermarket is playing a good corporate citizen role for society.

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However, SN does not significantly predict intention. This result may be explained by the majority of younger respondents in the study (32.4% 31–40-year olds and 24.1% 26–30-year olds), who are less likely to accept others’ opinions on less substantial decisions like hypermarket choice. The findings in this study imply that the readiness of consumers in CRM participation is primarily driven by their perception of and belief in the CRM campaign (attitude) as well as their ability and capacity to participate in a CRM campaign (perceived behavioural control).

When consumers feel that purchasing products from a hypermarket while donating to a worthy cause at the same time is a good idea, they have a favourable attitude towards the CRM campaign, and those not influenced by their social circle (i.e. insignificant relationship between subjective norms and CRM participation intention) will be more likely to join the campaign. Furthermore, this study also reveals that CRM participation intention has a significant and positive influence on hypermarket visit intention. This result is consistent with that of Bamberg et al. (2003), which indicated that when consumers have the intention to participate in a CRM campaign, they are more willing to visit a hypermarket that runs one.

6.1Theoretical Implications

This study makes several contributions to the existing theoretical knowledge. Firstly, it extends the use of TPB popularised by Ajzen (1991) by adding antecedents to attitude (i.e. AFM, CCI, CSRI and CCF) to assess their influence on CRM participation intention and hypermarket visit intention. Specifically, attitude and PBC are found to significantly influence CRM participation intention. However, unlike in Cavazos-Arroyo et al. (2017) and Luna et al. (2017), SN in this study is found to be insignificant, which implies that CRM participation intention is not influenced by the anticipation or agreement by specific important people. Although TPB has been widely applied

in various fields of study (e.g. Watanabe et al., 2015; Wu et al., 2016), TPB is scarcely used in the context of consumers’ participation intention regarding CRM. Therefore, this study shows how TPB can be used as a theoretical foundation to enhance the study of CRM participation intention.

Secondly, this study adds to the existing CRM literature by providing evidence that CCI (Lii & Lee, 2012), CSRI (Deng & Xu, 2017) and CCF (Van den Brink et al., 2006) significantly affect attitude towards CRM participation intention. This finding indicates that these factors can be used to influence consumers’ perception of CRM, providing evidence on these factors’ applicability in the hypermarket context involving the novel cause of supporting underprivileged individuals. Finally, this study indicates that CRM can help increase consumers’ hypermarket visit intention and shows how CRM can be used as a marketing strategy to enhance visit intention in the hypermarket context.

6.2 Managerial Implications

Overall, the findings of this study provide suggestions to the management of hypermarkets to increase consumers’ visit intention. Aside from possessing a strong retail marketing mix, hypermarkets that adopt a CRM campaign may draw in more consumers. The results indicate that variables such as CCI, CSRI and CCF play significant roles in influencing attitude towards CRM. In addition, attitude towards CRM participation has a greater effect size than SN and PBC. Therefore, efforts should be made in improving consumers’ attitude towards the CRM campaign. Attitude towards CRM can be improved if hypermarkets portray a positive CSR image, support a social cause that is consistent with their core business, products or brand image and when the consumer can associate with the hypermarket’s values.

To improve CSR image, hypermarkets can engage in more CSR initiatives that are genuine and visible to consumers. For example, they

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can engage in broader CSR initiatives targeting different salient stakeholders, such as employees, consumers and the local community. CSR for employees can be conducted by providing a quality working environment or by improving the quality of life of employees. CSR for consumers can be conducted by providing free transportation to older people for grocery shopping or by offering priority check-out lanes for senior citizens. CSR for the local community can be conducted by giving out basic necessities to the homeless, orphanages or old folks’ homes and by planning occasional cleaning activities in the parks used by local residents.

To build consumers’ ability and capability in participating in a CRM campaign, hypermarkets can apply CRM to all their products. For example, all purchased products could enable consumers to participate in CRM, regardless of the product being priced lower or higher and produced locally or abroad. That way, consumers are spared the hassle of finding products that are tied to the CRM campaign. Finally, hypermarkets can identify a social cause that is aligned with their core business or core values by talking to all non-government organizations (NGOs) operating within the vicinity. Supporting a local cause (NGO from the vicinity) may be more appealing than a non-local cause (La Ferle et al., 2013). In short, to increase consumers’ intention to visit a hypermarket, the manager may want to organize a CRM campaign that appeals to them.

6.3Limitation and Directions for Future Research

This study has several limitations, which readily provide avenues for future research. Firstly, this study’s explanatory power for CRM attitude is 37%, which indicates a 63% variance that is not explained. That is, some important factors are not included in the framework. Future studies could consider the factors that can improve the attractiveness of the CRM campaign. Examples of these factors are CRM campaign duration (Cui et al., 2003), donation proximity (Zhu et al., 2017)

and type of social cause supported (Lafferty & Edmondson, 2014). Secondly, the consumers’ hypermarket visit intention explanatory power was 41%, which shows that a 59% variance was not explained. Thus, future research could contemplate including additional factors into the model that may also influence consumers’ hypermarket visit intention, such as advertising (Anselmsson, 2006), location (Pan & Zinkhan, 2006) and price (Jin & Kim, 2003).

Thirdly, the insignificant effect of altruistic firm motives on attitude might be due to the fact that the impact of altruistic firm motives on attitude is overlapping with perceived corporate social responsibility (Table 3), which indicates that these two dimensions are very similar. Thus, future studies should consider including either one of these variables and should not include both because a high correlation between the two variables may nullify the explanatory power of one of them due to redundancy.

Fourthly, this study relies solely on the self-reported responses of the respondents on their CRM participation and hypermarket visit intention. Consumers usually speak positively about ethical issues but do not essentially follow through with the purchases they speak of (Cui et al., 2003). Therefore, the data may not truly reflect their behaviour. Future research is suggested to verify the relationship between CRM participation and hypermarket visit intention using the observation method based on actual behavioural data. Besides that, the experimental research method may also be employed to use a control group to compare against the experimental group. Fifthly, as the sample of this study is collected from Malaysia only, generalisability to other countries may be limited because of cultural differences in consumer behaviour. Future research can consider comparing the findings of this study with those from other countries to make a cross-cultural comparison. Lastly, the responses from respondents might have some degree of bias as social desirability was not measured and not detectable in this study. Hence, future studies

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could consider incorporating social desirability measurements in the questionnaire to measure consumers’ social desirability responses.

7 Conclusion

When consumers visit a hypermarket to purchase their daily groceries, they can decide to buy from a hypermarket that enables them to simultaneously contribute to a social cause. The empirical findings of this study show that hypermarkets that implement a CRM campaign attract more visits. Figure 2 presents the final research model of this study. This outcome

suggests that the use of CRM can enhance consumers’ intention to visit the hypermarket. Moreover, attitude towards the CRM campaign and PBC significantly affect consumers’ intention to participate in the CRM. Therefore, CRM participation intention can be improved if consumers are convinced of the CRM benefits and if the hypermarket makes it easy for consumers to participate in the CRM campaign. Factors such as CSRI, CCI and CCF affect consumers’ attitude towards CRM. Therefore, these factors should be considered by hypermarkets before and during designing a CRM campaign.

Figure 2 – Final Research Model

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Appendix 1 - Hypothetical CRM campaignAPPENDIX 1 - Hypothetical CRM campaign

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Appendix 2 – Independent T-Test on Gender, ANOVA on Highest Education Level and Monthly Income

Table 6 Independent T-Test on Gender

Levene’s Test for Equality of VarianceF Sig. t df Sig. (2-tailed)

Hypermarket Visit Intention Equal Variance Assumed 0.653 0.419 0.548 456 0.584

Equal Variance not Assumed 0.541 389.006 0.589CRM Participation Intention Equal Variance Assumed 0.857 0.355 -0.236 456 0.814

Equal Variance not Assumed -0.233 391.751 0.816

Table 7 Results of ANOVA between Hypermarket Visit Intention, CRM Participation Intention and Education Level

Groups n Mean SD F Sig.Hypermarket Visit Intention SPM or lower 118 5.218 0.944 2.312 0.075

Diploma 81 5.324 1.075Bachelor Degree 220 5.488 0.904

Master Degree and above 41 5.481 0.931

CRM Participation Intention SPM or lower 118 5.389 0.953 1.135 0.335Diploma 81 5.286 1.015

Bachelor Degree 220 5.281 0.991Master Degree and

above 41 5.427 0.930

Table 8 Results of ANOVA between Hypermarket Visit Intention, CRM Participation Intention and Monthly Income

Groups n Mean SD F Sig.Hypermarket Visit Intention

Below RM2000 48 5.396 1.041 1.009 0.428

RM2000 - RM4000 149 5.270 0.991RM4001 - RM6000 130 5.387 0.971RM6001 - RM8000 55 5.423 0.863RM8001 - RM10000 30 5.431 0.945RM10001 - RM12000 20 5.842 0.737RM12001 - RM14000 9 5.563 0.788RM14001 - RM16000 7 5.625 0.542

RM16001 or above 12 5.636 0.918CRM Participation Intention

Below RM2000 48 5.388 0.956 2.400 0.015

RM2000 - RM4000 149 5.578 1.006RM4001 - RM6000 130 5.237 1.000RM6001 - RM8000 55 5.342 0.933RM8001 - RM10000 30 5.177 0.980RM10001 - RM12000 20 5.3276 0.68499RM12001 - RM14000 9 5.8816 0.91806RM14001 - RM16000 7 6.1563 0.46170

RM16001 or above 12 5.4167 0.87560

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Appendix 3 - Questionnaire

Part I – Hypermarket Preferences

Please rank your hypermarket preferences from 1 to 5 for the following hypermarkets (1 – Most Preferable, 5 – Least Preferable).

¨ Giant ¨ Aeon Big ¨ NSK¨ Tesco ¨ Mydin

Assuming that “Your Preferred Hypermarket” (Part I) would like to implement a campaign that supports underprivileged individuals, please read the details carefully (APPENDIX 1) and answer the questions in Part II.

Part II – Cause-Related Marketing Campaign (Please refer to Appendix 1 Advertisement Board)

Strongly Disagree (SD) Disagree Somewhat

Disagree Neutral (N) Somewhat Agree Agree Strongly Agree (SA)

1 2 3 4 5 6 7

A: Altruistic Firm Motives

Based on the advertisement/campaign (Appendix 1), how would you describe “Your Preferred Hypermarket’s” MOTIVES for getting involved in the cause of “supporting underprivileged individuals”? Please circle only one number.

No. Items SD N SA

1 Pure (Sincere) 1 2 3 4 5 6 7

2 Unselfish 1 2 3 4 5 6 7

3 Caring 1 2 3 4 5 6 7

4 Society serving 1 2 3 4 5 6 7

5 Involved 1 2 3 4 5 6 7

6 Proactive 1 2 3 4 5 6 7

Based on the advertisement/campaign (Appendix 1), please indicate the statements that best describe your opinion based on the scales provided. Please circle only one number for each statement.

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B: Hypermarket’s Corporate Social Responsibility (CSR) Image

No. Items SD N SA

1 I think this hypermarket has a legitimate (genuine/sincere) interest in this cause. 1 2 3 4 5 6 72 This hypermarket is socially responsible. 1 2 3 4 5 6 73 This hypermarket is a good corporate citizen. 1 2 3 4 5 6 74 Helping others appears to be important to this hypermarket. 1 2 3 4 5 6 7

5 This promotion benefits “underprivileged individuals” more than it benefits this hypermarket. 1 2 3 4 5 6 7

C: Consumer-Company Identification (CCI)

No. Items SD N SA

1 This hypermarket’s principle is similar to my values. 1 2 3 4 5 6 72 When someone praises this hypermarket, it feels like a personal compliment. 1 2 3 4 5 6 73 When someone criticizes this hypermarket, it feels like a personal insult. 1 2 3 4 5 6 74 I am very interested in what others think about this hypermarket. 1 2 3 4 5 6 7

5 I am concerned about the related information and development of this hypermarket. 1 2 3 4 5 6 7

6 I will spread positive information on this hypermarket to others. 1 2 3 4 5 6 7

D: Perceived Company-Cause Fit

No. Items SD N SA

1 The “supporting underprivileged individuals” cause implemented by this hypermarket fits with the nature of its business. 1 2 3 4 5 6 7

2 The “supporting underprivileged individuals” cause implemented by this hypermarket is relevant to its business. 1 2 3 4 5 6 7

3 The “supporting underprivileged individuals” cause implemented by this hypermarket is appropriate for its brand image. 1 2 3 4 5 6 7

E: Intention to Participate in Cause-Related Marketing Campaign

No. Items SD N SA

1 I think this hypermarket’s campaign of “supporting underprivileged individuals’ is a good idea. 1 2 3 4 5 6 7

2I would be willing to participate in this hypermarket’s campaign of “supporting underprivileged individuals” by buying most of my groceries from this hypermarket.

1 2 3 4 5 6 7

3 I would consider purchasing products from this hypermarket that supports a social cause in order to provide help to the cause. 1 2 3 4 5 6 7

4It is likely that I would contribute to this hypermarket’s campaign of “supporting underprivileged individuals’ by buying most of my groceries from this hypermarket.

1 2 3 4 5 6 7

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Part III – Consumers Behaviour towards Cause-Related Marketing (CRM)

Please indicate the statements that best describe your opinion based on the scales provided. Please circle only one number for each statement.

Strongly Disagree (SD) Disagree Somewhat

Disagree Neutral (N) Somewhat Agree Agree Strongly Agree (SA)

1 2 3 4 5 6 7

A: Attitude

No. Items SD N SA

1 I like the idea of buying products from a hypermarket which donates part of its profits to a social cause or NGO. 1 2 3 4 5 6 7

2 I am willing to pay more for a product from a hypermarket if the hypermarket is donating part of the profits to a social cause. 1 2 3 4 5 6 7

3 If a hypermarket is donating part of its profits to a social cause, then I am more likely to buy its products. 1 2 3 4 5 6 7

4 Hypermarkets that advertise that they are donating part of their profits to a social cause are good corporate citizens. 1 2 3 4 5 6 7

B: Subjective Norms

No. Items SD N SA

1 The trend of purchasing products from a hypermarket that supports a social cause among people around me is increasing. 1 2 3 4 5 6 7

2 People around me generally believe that it is a good idea to purchase products from a hypermarket that supports a social cause. 1 2 3 4 5 6 7

3 My close friends and family members would appreciate it if I purchased products from a hypermarket that supports a social cause. 1 2 3 4 5 6 7

4 I would get all the required support (money, time, related information) from friends and family to purchase products from a hypermarket that supports a social cause. 1 2 3 4 5 6 7

C: Perceived Behavioural Control

No. Items SD N SA

1 I can make the decision independently to purchase products from a hypermarket that supports a social cause. 1 2 3 4 5 6 7

2 I have the financial capability to purchase products from a hypermarket that supports a social cause. 1 2 3 4 5 6 7

3 I have the time to go and purchase products from a hypermarket that supports a social cause. 1 2 3 4 5 6 7

4 I have complete information and awareness regarding where to purchase products from a hypermarket that supports a social cause. 1 2 3 4 5 6 7

5 Products from a hypermarket that supports a social cause are readily available in the location where I reside. 1 2 3 4 5 6 7

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Part IV – Hypermarket Visit Intention

Please indicate the statements that best describe your opinion based on the scales provided. Please circle only one number for each of the statements.

No. Items SD N SA

1 I would recommend this hypermarket that “supports underprivileged individuals” to someone who seeks my advice. 1 2 3 4 5 6 7

2 I would say positive things about this hypermarket that “supports underprivileged individuals” to other people. 1 2 3 4 5 6 7

3 I would encourage friends and relatives to shop at this hypermarket that “supports underprivileged individuals”. 1 2 3 4 5 6 7

4 I will continue to shop at this hypermarket that “supports underprivileged individuals” in the future. 1 2 3 4 5 6 7

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About the Authors: 1. [Kay Tze Hong, Doctor of Philosophy in Business Economics, University Putra Malaysia, Serdang, Malaysia. E-mail: [email protected]]ORCID

0000-0002-9336-41312. [Siew Imm Ng, Doctor of Philosophy in Management, University of Western Australia, Perth, Australia. E-mail: [email protected]]ORCID

0000-0002-6518-925X3. [Raja Nerina Raja Yusof, Doctor of Philosophy in Management, University of Otago, Dunedin, New Zealand. E-mail: [email protected]]ORCID

0000-0002-6768-28654. [Shivee Ranjanee Kaliappan, Doctor of Philosophy in Economics, International Islamic University of Malaysia, Kuala Lumpur, Malaysia. E-mail: [email protected]]ORCID

0000-0001-6953-7541

AcknowledgementThis research was supported by a Universiti Putra Malaysia Grant (GP-IPB/2014/9441000).

Contribution of each author

ContributionKay Tze Hong

Siew Imm Ng

Raja Nerina Raja Yusof

Shivee Ranjanee Kaliappan

1. Definition of research problem √ √ √ √

2. Development of hypotheses or research questions (empiricalstudies) √ √ √

3. Development of theoretical propositions (theoretical work) √ √

4. Theoretical foundation/Literature review √

5. Definition of methodological procedures √ √ √

6. Data collection √

7. Statistical analysis √

8. Analysis and interpretation of data √

9. Critical revision of the manuscript √ √ √

10. Manuscript writing √ √

11. Other (please specify which)

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